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faturesdeflections
feature deflections identification
- 2010-02-20 04:16:25下载
- 积分：1
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D3DXMatrixRotationAxis_analysis
D3DXMatrixRotationAxis 数学原理解析
Axis To Axis 的矩阵生成
介绍广告版的复杂搭建 原理
附录 Matlab 和 C++ 代码
(D3DXMatrixRotationAxis mathematical theory of matrix analysis Axis To Axis generate complex structures introduced principles of billboards Appendix Matlab and C++ code)
- 2010-05-23 15:38:38下载
- 积分：1
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problem1structures
MATLAB structures provide a way to collect arrays of different types and sizes
in a single array. The following codes show how this can be made for problem1.m.
One of the most interesting features is that the argument passing to functions is
simplified.
MATLAB codes for Finite Element Analysis
problem1.m
antonio ferreira 2008
- 2013-10-01 19:07:56下载
- 积分：1
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code-matlab
ocr system for Identification number by moment invariant
- 2012-12-29 16:54:43下载
- 积分：1
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RGBtoLab
RGB color channel to XYZ channel.
XYZ channel to CIELab channel.
- 2013-09-02 17:23:20下载
- 积分：1
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GalileocodinginRaily
说明： 瑞利衰落信道下高斯干扰下的GALILEO编码译码系统性能分析以及误码率的仿真(Rayleigh fading channels under Gaussian interference GALILEO codec system performance analysis and simulation BER)
- 2008-11-25 17:20:44下载
- 积分：1
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zuidabihebing
选择适合并和最大比合并的性能比较分析。有详细的代码供参考(Choose to suit and the comparative analysis and maximum ratio combining performance.Has a detailed code for your reference)
- 2014-12-10 13:09:59下载
- 积分：1
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HCDC
直流输电系统的matlab仿真。包括VSC LCC等控制方式。(Matlab simulation of HVDC system. Including VSC LCC and other control methods.)
- 2014-12-10 22:21:21下载
- 积分：1
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111
内弹道计算程序，准确描述了内弹道过程，通俗易懂(Interior ballistics calculation program, an accurate description of the interior ballistics process, straightaway)
- 2013-12-03 21:13:08下载
- 积分：1
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knn1
K最邻近密度估计技术是一种分类方法，不是聚类方法。
不是最优方法，实践中比较流行。
通俗但不一定易懂的规则是：
1.计算待分类数据和不同类中每一个数据的距离（欧氏或马氏）。
2.选出最小的前K数据个距离，这里用到选择排序法。
3.对比这前K个距离，找出K个数据中包含最多的是那个类的数据，即为待分类数据所在的类。(K nearest neighbor density estimation is a classification method, not a clustering method.
It is not the best method, but it is popular in practice.
Popular but not necessarily understandable rule is:
1. calculate the distance between the data to be classified and the data in each other (Euclidean or Markov).
2. select the minimum distance from the previous K data, where the choice sorting method is used.
3. compare the previous K distances to find out which K data contains the most data of that class, that is, the class to which the data to be classified is located.)
- 2017-08-09 21:06:38下载
- 积分：1
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